A review of task scheduling in cloud computing based on nature-inspired optimization algorithm

The advent of the cloud computing paradigm allowed multiple organizations to move, compute, and host their applications in the cloud environment, enabling seamless access to a wide range of services with minimal effort. An efficient and dynamic task scheduler is required to handle concurrent user requests for cloud services using various heterogeneous and diversified resources. Improper scheduling can lead to challenges with under or over-utilization of resources, which could waste cloud resources or degrade service performance. Nature-inspired optimization techniques have been proven effective at solving scheduling problems. This paper accomplishes a review of nature-inspired optimization techniques for scheduling tasks in cloud computing. A novel classification taxonomy and comparative review of these techniques in cloud computing are presented in this research. The taxonomy of nature-inspired scheduling techniques is categorized as per the scheduling algorithms, nature of the scheduling problem, type of tasks, the primary objective of scheduling, task-resource mapping scheme, scheduling constraint, and testing environment. Additionally, guidelines for future research issues are also provided, which should undoubtedly benefit researchers and practitioners as well as open the door for newcomers eager to pursue their glory in the field of cloud task scheduling.